EngineX/xc-llm-ascend
3
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

[Doc][Misc] Restructure tutorial documentation (#6501)

Browse Source 
### What this PR does / why we need it?

This PR refactors the tutorial documentation by restructuring it into
three categories: Models, Features, and Hardware. This improves the
organization and navigation of the tutorials, making it easier for users
to find relevant information.

- The single `tutorials/index.md` is split into three separate index
files:
  - `docs/source/tutorials/models/index.md`
  - `docs/source/tutorials/features/index.md`
  - `docs/source/tutorials/hardwares/index.md`
- Existing tutorial markdown files have been moved into their respective
new subdirectories (`models/`, `features/`, `hardwares/`).
- The main `index.md` has been updated to link to these new tutorial
sections.

This change makes the documentation structure more logical and scalable
for future additions.

### Does this PR introduce _any_ user-facing change?

Yes, this PR changes the structure and URLs of the tutorial
documentation pages. Users following old links to tutorials will
encounter broken links. It is recommended to set up redirects if the
documentation framework supports them.

### How was this patch tested?

These are documentation-only changes. The documentation should be built
and reviewed locally to ensure all links are correct and the pages
render as expected.

- vLLM version: v0.15.0
- vLLM main: https://github.com/vllm-project/vllm/commit/v0.15.0

Signed-off-by: wangxiyuan <wangxiyuan1007@gmail.com>
This commit is contained in:
wangxiyuan
2026-02-10 15:03:35 +08:00
committed by GitHub
parent 77305df398
commit 7d4833bce9
39 changed files with 159 additions and 151 deletions
Download Patch File Download Diff File Expand all files Collapse all files

20
docs/source/installation.md
View File

@@ -136,7 +136,7 @@ pip config set global.index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/si
```bash
# For torch-npu dev version or x86 machine
pip config set global.extra-index-url "https://download.pytorch.org/whl/cpu/ https://mirrors.huaweicloud.com/ascend/repos/pypi"
pip config set global.extra-index-url "https://download.pytorch.org/whl/cpu/"
```
Then you can install `vllm` and `vllm-ascend` from **pre-built wheel**:
@@ -187,12 +187,12 @@ Supported images as following.
| image name | Hardware | OS |
|-|-|-|
| image-tag | Atlas A2 | Ubuntu |
| image-tag-openeuler | Atlas A2 | openEuler |
| image-tag-a3 | Atlas A3 | Ubuntu |
| image-tag-a3-openeuler | Atlas A3 | openEuler |
| image-tag-310p | Atlas 300I | Ubuntu |
| image-tag-310p-openeuler | Atlas 300I | openEuler |
| vllm-ascend:<image-tag> | Atlas A2 | Ubuntu |
| vllm-ascend:<image-tag>-openeuler | Atlas A2 | openEuler |
| vllm-ascend:<image-tag>-a3 | Atlas A3 | Ubuntu |
| vllm-ascend:<image-tag>-a3-openeuler | Atlas A3 | openEuler |
| vllm-ascend:<image-tag>-310p | Atlas 300I | Ubuntu |
| vllm-ascend:<image-tag>-310p-openeuler | Atlas 300I | openEuler |
:::{dropdown} Click here to see "Build from Dockerfile"
or build IMAGE from **source code**:
@@ -258,7 +258,7 @@ prompts = [
# Create a sampling params object.
sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
# Create an LLM.
llm = LLM(model="Qwen/Qwen2.5-0.5B-Instruct")
llm = LLM(model="Qwen/Qwen3-0.6B")
# Generate texts from the prompts.
outputs = llm.generate(prompts, sampling_params)
@@ -277,7 +277,7 @@ python example.py
If you encounter a connection error with Hugging Face (e.g., `We couldn't connect to 'https://huggingface.co' to load the files, and couldn't find them in the cached files.`), run the following commands to use ModelScope as an alternative:
```bash
export VLLM_USE_MODELSCOPE = true
export VLLM_USE_MODELSCOPE=true
pip install modelscope
python example.py
```
@@ -292,7 +292,7 @@ INFO 02-18 08:49:58 __init__.py:34] set environment variable VLLM_PLUGINS to con
INFO 02-18 08:49:58 __init__.py:42] plugin ascend loaded.
INFO 02-18 08:49:58 __init__.py:174] Platform plugin ascend is activated
INFO 02-18 08:50:12 config.py:526] This model supports multiple tasks: {'embed', 'classify', 'generate', 'score', 'reward'}. Defaulting to 'generate'.
INFO 02-18 08:50:12 llm_engine.py:232] Initializing a V0 LLM engine (v0.7.1) with config: model='./Qwen2.5-0.5B-Instruct', speculative_config=None, tokenizer='./Qwen2.5-0.5B-Instruct', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, device_config=npu, decoding_config=DecodingConfig(guided_decoding_backend='xgrammar'), observability_config=ObservabilityConfig(otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=0, served_model_name=./Qwen2.5-0.5B-Instruct, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=False, chunked_prefill_enabled=False, use_async_output_proc=True, disable_mm_preprocessor_cache=False, mm_processor_kwargs=None, pooler_config=None, compilation_config={"splitting_ops":[],"compile_sizes":[],"cudagraph_capture_sizes":[256,248,240,232,224,216,208,200,192,184,176,168,160,152,144,136,128,120,112,104,96,88,80,72,64,56,48,40,32,24,16,8,4,2,1],"max_capture_size":256}, use_cached_outputs=False,
INFO 02-18 08:50:12 llm_engine.py:232] Initializing a V0 LLM engine (v0.7.1) with config: model='./Qwen3-0.6B', speculative_config=None, tokenizer='./Qwen3-0.6B', skip_tokenizer_init=False, tokenizer_mode=auto, revision=None, override_neuron_config=None, tokenizer_revision=None, trust_remote_code=False, dtype=torch.bfloat16, max_seq_len=32768, download_dir=None, load_format=auto, tensor_parallel_size=1, pipeline_parallel_size=1, disable_custom_all_reduce=False, quantization=None, enforce_eager=False, kv_cache_dtype=auto, device_config=npu, decoding_config=DecodingConfig(guided_decoding_backend='xgrammar'), observability_config=ObservabilityConfig(otlp_traces_endpoint=None, collect_model_forward_time=False, collect_model_execute_time=False), seed=0, served_model_name=./Qwen3-0.6B, num_scheduler_steps=1, multi_step_stream_outputs=True, enable_prefix_caching=False, chunked_prefill_enabled=False, use_async_output_proc=True, disable_mm_preprocessor_cache=False, mm_processor_kwargs=None, pooler_config=None, compilation_config={"splitting_ops":[],"compile_sizes":[],"cudagraph_capture_sizes":[256,248,240,232,224,216,208,200,192,184,176,168,160,152,144,136,128,120,112,104,96,88,80,72,64,56,48,40,32,24,16,8,4,2,1],"max_capture_size":256}, use_cached_outputs=False,
Loading safetensors checkpoint shards: 0% Completed | 0/1 [00:00<?, ?it/s]
Loading safetensors checkpoint shards: 100% Completed | 1/1 [00:00<00:00, 5.86it/s]
Loading safetensors checkpoint shards: 100% Completed | 1/1 [00:00<00:00, 5.85it/s]